Reconstruction of probabilistic S-N curves under fatigue life following lognormal distribution with given confidence

When the historic probabilistic S-N curves are given under special survival probability and confidence levels and there is no possible to re-test, fatigue reliability analysis at other levels can not be done except for the special levels. Therefore, the wide applied curves are expected. Monte Carlo reconstruction methods of the test data and the curves are investigated under fatigue life following lognormal distribution. To overcome the non-conservative assessment of existent man-made enlarging the sample size up to thousands, a simulation policy is employed to address the true production where the sample size is controlled less than 20 for material specimens, 10 for structural component specimens and the errors matching the statistical parameters are less than 5 percent. Availability and feasibility of the present methods have been indicated by the reconstruction practice of the test data and curves for 60Si2Mn high strength spring steel of railway industry.

A Novel Contour Tracing Algorithm for Object Shape Reconstruction Using Parametric Curves

Parametric curves such as Bézier and B-splines, originally developedfor the design of automobile bodies, are now also used in image processing andcomputer vision. For example, reconstructing an object shape in an image,including different translations, scales, and orientations, can be performedusing these parametric curves. For this, Bézier and B-spline curves can be generatedusing a point set that belongs to the outer boundary of the object. Theresulting object shape can be used in computer vision fields, such as searchingand segmentation methods and training machine learning algorithms. Theprerequisite for reconstructing the shape with parametric curves is to obtainsequentially the points in the point set. In this study, a novel algorithm hasbeen developed that sequentially obtains the pixel locations constituting theouter boundary of the object. The proposed algorithm, unlike the methods inthe literature, is implemented using a filter containing weights and an outercircle surrounding the object. In a binary format image, the starting point ofthe tracing is determined using the outer circle, and the next tracing movementand the pixel to be labeled as the boundary point is found by the filter weights.Then, control points that define the curve shape are selected by reducing thenumber of sequential points. Thus, the Bézier and B-spline curve equationsdescribing the shape are obtained using these points. In addition, differenttranslations, scales, and rotations of the object shape are easily provided bychanging the positions of the control points. It has also been shown that themissing part of the object can be completed thanks to the parametric curves.

RECONSTRUCTION OF SYMMETRIC B-SPLINE CURVES AND SURFACES

A method to reconstruct symmetric B-spline curves and surfaces is presented. The symmetry property is realized by using symmetric knot vector and symmetric control points. Firstly, data points are divided into two parts based on the symmetry axis or symmetry plane extracted from data points. Then the divided data points are parameterized and a symmetric knot vector is selected in order to get symmetric B-spline basis functions. Constraint equations regarding the control points are deduced to keep the control points of the B-spline curve or surface to be symmetric with respect to the extracted symmetry axis or symmetry plane. Lastly, the constrained least squares fitting problem is solved with the Lagrange multiplier method. Two examples from industry are given to show that the proposed method is efficient, robust and able to meet the general engineering requirements.

Lutetium in prostate cancer: Reconstruction of patient-level data from published trials and generation of a multi-trial Kaplan-Meier curve

BACKGROUND Lutetium has been shown to be an important potential innovation in pre-treated metastatic castration-resistant prostate cancer.Two clinical trials have evaluated lutetium thus far(therap and vision with 99 and 385 patients,respectively),but their results are discordant.AIM To synthetize the available evidence on the effectiveness of lutetium in pre-treated metastatic castration-resistant prostate cancer;and to test the application of a new artificial intelligence technique that synthetizes effectiveness based on reconstructed patient-level data.METHODS We employed a new artificial intelligence method(shiny method)to pool the survival data of these two trials and evaluate to what extent the lutetium cohorts differed from one another.The shiny technique employs an original reconstruction of individual patient data from the Kaplan-Meier curves.The progression-free survival graphs of the two lutetium cohorts were analyzed and compared.RESULTS The hazard ratio estimated was in favor of the vision trial;the difference was statistically significant(P<0.001).These results indicate that further studies on lutetium are needed because the survival data of the two trials published thus far are conflicting.CONCLUSION Our study confirms the feasibility of reconstructing patient-level data from survival graphs in order to generate a survival statistics.

3D reconstruction of complex curved objects from line drawings

An active research topic in computer vision and graphics is developing algorithms that can reconstruct the 3D surface of curved objects from line drawings. There are a number of algorithms have been dedicated to solve this problem, but they can＇t solve this problem when the geometric structure of a curved object becomes complex. This paper proposes a novel approach to reconstructing a complex curved 3D object from single 2D line drawings. Our approach has three steps： （1） decomposing a complex line drawing into several simpler line drawings and transforming them into polyhedron; （2） reconstructing the 3D wireframe of curved object from these simpler line drawings and generating the curved faces; （3） combining the 3D objects into the complete objects. A number of examples are given to demonstrate the ability of our approach to successfully perform reconstruction of curved objects which are more complex than previous methods.

MICRO-ROBOT FOR MEASUREMENT AND THREE-DIMENSION RECONSTRUCTION OF MICROPIPES

The presented system consists of field devices, a control system and a host computer system. The field devices, which are composed of an in-pipe micro-robot, a displacement sensor, a curvature sensor, and an inner surface measurement unit, can go into the pipe to get the data of displace- ment and axis curvature, and the shape data of the inner surface. With the conic-shape laser beam shot by the inner surface measurement unit, the intersectional curve between the laser beam and the inner-surface of the tested pipe can be calculated in the local coordination system （LCS） of the inner surface measurement unit. The relation between the LCS and the global coordination system （GCS） can be deduced, too. After the robot reaches the end of the pipe, all measured intersectional curves can be translated into the same coordination system to become a point cloud of the inner surface of the pipe according to the relations between LCS and GCS. Depending on this points cloud, the CAD model of the inner surface of the pipe can be reconstructed easily with reverse engineering tools, and the feature of flaw of the pipe can be obtained with flaw analysis tools.

Randomized Kaczmarz algorithm for CT reconstruction

The order of the projection in the algebraic reconstruction technique(ART)method has great influence on the rate of the convergence.Although many scholars have studied the order of the projection,few theoretical proofs are given.Thomas Strohmer and Roman Vershynin introduced a randomized version of the Kaczmarz method for consistent,and over-determined linear systems and proved whose rate does not depend on the number of equations in the systems in 2009.In this paper,we apply this method to computed tomography(CT)image reconstruction and compared images generated by the sequential Kaczmarz method and the randomized Kaczmarz method.Experiments demonstrates the feasibility of the randomized Kaczmarz algorithm in CT image reconstruction and its exponential curve convergence.

Curve interpolation model for visualising disjointed neural elements

Neuron cell are built from a myriad of axon and denddte structures. It transmits electrochemical signals between the brain and the nervous system. Three-dimensional visualization of neuron structure could help to facilitate deeper understanding of neuron and its models. An accurate neuron model could aid understanding of brain＇s functionalities, diagnosis and knowledge of entire nervous system. Existing neuron models have been found to be defective in the aspect of realism. Whereas in the actual biological neuron, there is continuous growth as the soma extending to the axon and the dendrite; but, the current neuron visualization models present it as disjointed segments that has greatly mediated effective realism. In this research, a new reconstruction model comprising of the Bounding Cylinder, Curve Interpolation and Gouraud Shading is proposed to visualize neuron model in order to improve realism. The reconstructed model is used to design algorithms for generating neuron branching from neuron SWC data. The Bounding Cylinder and Curve Interpolation methods are used to improve the connected segments of the neuron model using a series of cascaded cylinders along the neuron＇s connection path. Three control points are proposed between two adjacent neuron segments. Finally, the model is rendered with Gouraud Shading for smoothening of the model surface. This produce a near-perfection model of the natural neurons with attended realism. The model is validated by a group of bioinformatics analysts＇ responses to a predefined survey. The result shows about 82% acceptance and satisfaction rate.

Rollback reconstruction for TDC enhanced perfusion imaging

Tomographic perfusion imaging is a significant imaging modality for stroke diagnosis.However,the low rotational speed of the C-arm(6–8 s per circle)is a challenge for applying perfusion imaging in C-arm cone beam computed tomography(CBCT).Traditional reconstruction methods cannot remove the artifacts caused by the slow rotational speed or acquire enough sample points to restore the time density curve(TDC).This paper presents a dynamic rollback reconstruction method for CBCT.The proposed method can improve the temporal resolution by increasing the sample points used for calculating the TDC.Combined with existing techniques,the algorithm allows slow-rotating scanners to be used for perfusion imaging purposes.In the experiments,the proposed method was compared with other dynamic reconstruction algorithms based on standard reconstruction and the temporal interpolation approach.The presented algorithm could improve the temporal resolution without increasing the X-ray exposure time or contrast agent.

A Fourth-Order Unstructured NURBS-Enhanced Finite Volume WENO Scheme for Steady Euler Equations in Curved Geometries

In Li and Ren(Int.J.Numer.Methods Fluids 70:742–763,2012),a high-order k-exact WENO finite volume scheme based on secondary reconstructions was proposed to solve the two-dimensional time-dependent Euler equations in a polygonal domain,in which the high-order numerical accuracy and the oscillations-free property can be achieved.In this paper,the method is extended to solve steady state problems imposed in a curved physical domain.The numerical framework consists of a Newton type finite volume method to linearize the nonlinear governing equations,and a geometrical multigrid method to solve the derived linear system.To achieve high-order non-oscillatory numerical solutions,the classical k-exact reconstruction with k=3 and the efficient secondary reconstructions are used to perform the WENO reconstruction for the conservative variables.The non-uniform rational B-splines(NURBS)curve is used to provide an exact or a high-order representation of the curved wall boundary.Furthermore,an enlarged reconstruction patch is constructed for every element of mesh to significantly improve the convergence to steady state.A variety of numerical examples are presented to show the effectiveness and robustness of the proposed method.

Efficient reconstruction of non-simple curves

We present a novel algorithm to reconstruct curves with self-intersections and multiple parts from unorganized strip-shaped points,which may have different local shape scales and sampling densities.We first extract an initial curve,a graph composed of polylines,to model the different structures of the points.Then a least-squares optimization is used to improve the geometric approximation.The initial curve is extracted in three steps:anisotropic farthest point sampling with an adaptable sphere,graph construction followed by non-linear region identification,and edge refinement.Our algorithm produces faithful results for points sampled from non-simple curves without pre-segmenting them.Experiments on many simulated and real data demonstrate the efficiency of our method,and more faithful curves are reconstructed compared to other existing methods.

An Approximating Algorithm on Reconstruction of Complicated Curved Surface

An approximating algorithm on handling 3-D points cloud data was discussed for reconstruction of complicated curved surface. In this algorithm, the coordinate information of nodes both in internal and external regions of partition interpolation was used to realize minimized least squares approximation error of surface fitting. The changes between internal and external interpolation regions are continuous and smooth. Meanwhile, surface shape has properties of local controllability, variation reduction, and convex hull. The practical example shows that this algorithm possesses a higher accuracy of curved surface reconstruction and also improves the distortion of curved surface reconstruction when typical approximating algorithms and unstable operation are used.

股前外侧穿支皮瓣术前CT血管成像扫描及重建方案研究

目的:股前外侧皮瓣是一种用于头颈部缺损重建的多功能骨干皮瓣,其穿支血管的位置、走向和来源评估对制定合理的手术计划中至关重要。小视野(Small FOV)技术可以缩小重建视野,增加图像分辨率,提升对穿支血管显示的空间分辨率;双阶段造影剂注射法增强末梢血管的充盈压力;多平面重建(MPR)对感兴趣区域进行冠状位重组,观察旋股外动脉远端各皮支血管分布;曲面重建(CPR)生成穿支血管的曲面图像,将穿支血管曲面路径与旋股外动脉主干容积成像图像融合,确定穿支血管的位置及其走行。本研究旨在通过各种计算机断层血管造影(CTA)扫描和后处理技术提高皮瓣穿支血管的可视化。方法:研究组为我院耳鼻喉头颈外科于2018年1月至2021年8月对13例头颈部肿瘤术后缺损患者行皮瓣术前CTA改进扫描方案。对照组选取首都医科大学附属北京友谊医院放射科2020年9月至2023年4月,为进行双下肢动脉CT非能谱血管成像检查的13例患者,股动脉及其分支血管无明显病变。对两组血管成像质量进行主观评价,并对旋股外动脉的对比噪声比(CNR)和信噪比(SNR)进行客观评价。结果:研究组SNR较对照组稍高,但两组差别无统计学意义。研究组CNR均值为18.25±7.38,对照组CNR均值为7.26±2.64,研究组CNR明显高于对照组,两组差别有统计学意义。研究组与对照组图像质量主观评价无差异。研究组术前在CTA上检测到的穿支血管100%在手术中得到证实。结论:多种技术综合应用增加皮支血管与周围组织的对比,获得满意的CT图像质量,提高图像分析的准确性,给临床医生分析供血血管的位置、走行和来源提供了更好的技术支持。

MRI三维重建技术在颅神经血管压迫综合征中的应用价值

目的探讨MRI三维重建技术在颅神经血管压迫综合征责任血管识别和神经受压判定中的应用价值。方法在微血管减压术前对91例三叉神经痛及72例面肌痉挛患者行桥小脑角池段颅神经和血管成像,将获得的MRI原始数据分别进行二维和三维水平(曲面及仿真内窥镜)重建,多维度评价责任血管的数目、来源和颅神经受压程度,并将影像诊断结果与术中所见进行比较。结果三维重建技术对三叉神经痛责任血管的正确识别率为95.6%,对血管压迫神经判定的准确性为94.5%。此技术对面肌痉挛责任血管的正确识别率为91.7%,对血管压迫神经判定的准确性为89.5%。三维重建技术对责任血管与颅神经单纯性接触的判定准确率明显高于二维图像(P<0.05)。结论MRI三维重建技术可以提高责任血管识别的正确率,更加准确地检测颅神经受压程度,对于多支责任血管造成的颅神经复杂性压迫更为适用。

基于小波与反褶积结合的薄互层岩性界面识别方法

准噶尔盆地莫西庄地区三工河组二段岩性复杂多样、变化快,单砂岩体中薄层岩性频繁互层,存在较强的岩性、物性、含油非均质性特征。精细划分薄互层岩性并识别其分层界面是开展储层识别、流体解释及有效储层厚度确立等重要的前提工作。为了精确地识别薄互层岩性的分层界面,从测井信息采集分辨率与信号分析角度出发,提出了基于小波与反褶积相结合的薄互层岩性分层界面识别方法。首先,利用小波变换多尺度分解和重构原理,对自然伽马测井曲线进行高、低频分解,提取出反映地层岩性变化的有效信号与高频噪声;然后,对有效信号进行重构,构建一条去除噪声能够表征更接近真实地层信息的自然伽马测井曲线;最后,利用反褶积方法对重构的自然伽马测井曲线进行高分辨率处理,很大程度上提高了自然伽马测井曲线响应薄层岩性的纵向分辨率。经实例井取心岩性资料验证,利用该方法处理得到高分辨率自然伽马测井曲线的形态与数值特征能够有效地提高单砂岩体中多套薄互层岩性分层界面识别的精度,为莫西庄三工河组二段储层有效性精细评价提供了依据。

基于在机测量的曲面共形电路3D打印误差补偿方法

基于3D打印技术制备曲面共形电路具有广阔的应用前景,然而,由于曲面基材加工误差和导电线路定位误差的影响,导致曲面电路3D打印头高度难以精确控制,进而影响打印精度。为此,本文以气动式直写打印为研究对象,提出了一种“在机测量+线路模型重构”的打印头高度误差补偿方法。设计了一种曲率自适应测量点选取方法,利用NURBS曲线反算法对测量数据进行重构,还原真实线路模型。通过生成真实线路的打印轨迹,替换原始理论打印轨迹,补偿了打印头高度误差。自主搭建了一套集成了在机测量系统的曲面共形电路3D打印平台,设计了直线、圆弧与NURBS自由曲线3种形状的线路,进行补偿前后电路打印的对比实验。结果表明,未进行补偿前,在线路曲率较大的地方,线路在基板上的波峰处会产生拉丝现象,波谷处会产生堆叠现象,而补偿后的导线线宽比较均匀;进一步对每条导线的电阻进行测量,发现各条线路补偿前的电阻值波动较大,补偿后的电路的电阻值均匀,且相较补偿前平均降低65.99%,最大电阻降幅达85.75%。

多属性神经网络反演在重力流储层预测中的应用——以歧口凹陷歧南斜坡沙一段为例

歧口凹陷歧南斜坡沙一段属于典型的重力流水道沉积,受湖盆深陷扩张、沉积坡度陡等因素影响,各层砂体普遍发育,但纵向相互叠置、横向变化大,地震属性分析对纵向相互叠置砂体的区分能力较差、精度不高。基于特征曲线重构的多属性神经网络反演技术先通过叠后地震资料拓频处理,提高薄层砂岩识别能力,再利用基于高阶统计量的时频分析技术构建五级层序格架,细化地质研究对象,最后采用基于GR曲线重构的多属性神经网络反演进行储层预测。该技术使得砂体叠置区分辨能力更强,边界刻画更清晰,提高了反演结果的精度和准确性,实践证实储层预测符合率可达到80%以上,为纵横向变化大的砂体分布预测提供了一种新的技术思路。

基于计算机视觉的舰船模型三维重建方法

为保证舰船模型三维重建的完整性以及细节程度,提出基于计算机视觉的舰船模型三维重建方法。基于双目立体视觉计算全局舰船目标点云坐标,生成舰船全局的三维点云数据;多视角点云配准方法对该数据进行配准后,输入多尺度特征递归卷积的稠密点云重建网络模型中,通过该模型生成舰船模型三维深度图,在此基础上,利用运动结构法完成舰船深度图中的三维曲线重建,对舰船模型进行颜色渲染,输出舰船模型三维重建结果。测试结果显示,该方法能够完成不同图像之间对应点的可靠匹配,确定各点的坐标位置;三维重建后模型的空间偏差均在0.015以下;能够较好地完成舰船结构的重建,重建后舰船模型的完整性较好,清晰呈现舰船的结构细节。

基于电量-功率的多模态映射的长预见期光伏集群功率预测

现有光伏功率预测方法的时间尺度大多短于7 d,长预见期时间尺度下建立的时序预测模型的拟合能力难以满足需求。提出一种基于电量-功率多模态映射的长预见期(8~15 d)光伏集群功率预测方法。对天气进行分型并提取粗粒度下的光伏出力特性,在此基础上对细粒度电量进行预测;基于出力特性构建约束,将预测电量还原为功率,实现长预见期下光伏功率的有效预测。将所提方法应用于甘肃某光伏集群,预测精度提升了6.58个百分点,在实现长预见期预测的同时,提高了可靠性。

“基于光纤传感器的平面曲线重建算法建模”评阅综述

针对基于光纤传感器的平面曲线重建算法问题,首先利用波长与曲率之间的关系估算传感器位置的曲率,采用三次样条插值算法获取更多的曲率,利用斜率递推模型或者微分方程模型估计平面曲线坐标;进一步,对已知曲线先等距采样,再重构曲线方程,利用范数来评价重构算法的有效性;最后对2024年“华中杯”大学生数学建模挑战赛C题参赛论文的整体情况予以简要评述.